Gabriel Dulac-Arnold

发表

Differentiable Deep Clustering with Cluster Size Constraints pdf

Jean-Philippe Vert, Aude Genevay, Gabriel Dulac-Arnold, 2019, ArXiv.

Sequential approaches for learning datum-wise sparse representations

Patrick Gallinari, Gabriel Dulac-Arnold, Philippe Preux, 2012, Machine Learning.

An empirical investigation of the challenges of real-world reinforcement learning pdf

Nir Levine, Gabriel Dulac-Arnold, Sven Gowal, 2020, ArXiv.

Deep Q-learning From Demonstrations

Tom Schaul, Andrew Sendonaris, Joel Z. Leibo, 2017, AAAI.

Sequentially Generated Instance-Dependent Image Representations for Classification pdf

Matthieu Cord, Ludovic Denoyer, Nicolas Thome, 2014, ICLR.

Deep multi-class learning from label proportions pdf

Lucas Beyer, Jean-Philippe Vert, Marco Cuturi, 2019, ArXiv.

Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization

Patrick Gallinari, Gabriel Dulac-Arnold, Philippe Preux, 2012, ECML/PKDD.

Reinforcement Learning in Large Discrete Action Spaces pdf

Peter Sunehag, Gabriel Dulac-Arnold, Richard Evans, 2015, ArXiv.

Model-Based Offline Planning pdf

Gabriel Dulac-Arnold, Arthur Argenson, 2020, ArXiv.

Lecture Séquentielle de Documents pour la Classification

Ludovic Denoyer, Patrick Gallinari, Gabriel Dulac-Arnold, 2012, CORIA.

A Geometric Perspective on Self-Supervised Policy Adaptation pdf

Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski, 2020, ArXiv.

The Predictron: End-To-End Learning and Planning pdf

Tom Schaul, David Silver, Matteo Hessel, 2016, ICML.

Datum-Wise Classification: A Sequential Approach to Sparsity pdf

Ludovic Denoyer, Patrick Gallinari, Gabriel Dulac-Arnold, 2011, ECML/PKDD.

Text Classification: A Sequential Reading Approach pdf

Patrick Gallinari, Gabriel Dulac-Arnold, Ludovic Denoyer, 2011, ECIR.

RL Unplugged: Benchmarks for Offline Reinforcement Learning pdf

Nando de Freitas, Alexander Novikov, Mohammad Norouzi, 2020, ArXiv.

Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions pdf

Peter Sunehag, Gabriel Dulac-Arnold, Yori Zwols, 2015, ArXiv.

Deep Reinforcement Learning in Large Discrete Action Spaces

Richard Evans, Peter Sunehag, Timothy A. Mann, 2015, 1512.07679.

The first AI-based mobile application for antibiotic resistance testing

Christophe Ambroise, Jean-Philippe Vert, Gabriel Dulac-Arnold, 2020, bioRxiv.

Learning from Demonstrations for Real World Reinforcement Learning pdf

Tom Schaul, Andrew Sendonaris, Joel Z. Leibo, 2017, ArXiv.

RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning

Sergio Gomez Colmenarejo, Nando de Freitas, Alexander Novikov, 2020, NeurIPS.

Challenges of Real-World Reinforcement Learning pdf

Gabriel Dulac-Arnold, Todd Hester, Daniel J. Mankowitz, 2019, ArXiv.

A Metric Space Perspective on Self-Supervised Policy Adaptation

Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski, 2021, IEEE Robotics and Automation Letters.

Residual Reinforcement Learning from Demonstrations pdf

Cordelia Schmid, Jean Ponce, Julien Mairal, 2021, ArXiv.

Learning Dynamics Models for Model Predictive Agents pdf

Yuval Tassa, Gabriel Dulac-Arnold, Nicolas Heess, 2021, ArXiv.

Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

Nir Levine, Gabriel Dulac-Arnold, Sven Gowal, 2021, Machine Learning.

Learning to run a Power Network Challenge: a Retrospective Analysis pdf

Isabelle Guyon, Mariette Awad, Patrick Panciatici, 2020, NeurIPS.